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https://issues.apache.org/jira/browse/SPARK-7160?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Armbrust updated SPARK-7160:
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Priority: Critical (was: Major)
Target Version/s: 1.5.0
Shepherd: Michael Armbrust
> Support converting DataFrames to typed RDDs.
> --------------------------------------------
>
> Key: SPARK-7160
> URL: https://issues.apache.org/jira/browse/SPARK-7160
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: Ray Ortigas
> Assignee: Ray Ortigas
> Priority: Critical
>
> As a Spark user still working with RDDs, I'd like the ability to convert a
> DataFrame to a typed RDD.
> For example, if I've converted RDDs to DataFrames so that I could save them
> as Parquet or CSV files, I would like to rebuild the RDD from those files
> automatically rather than writing the row-to-type conversion myself.
> {code}
> val rdd0 = sc.parallelize(Seq(Food("apple", 1), Food("banana", 2),
> Food("cherry", 3)))
> val df0 = rdd0.toDF()
> df0.save("foods.parquet")
> val df1 = sqlContext.load("foods.parquet")
> val rdd1 = df1.toTypedRDD[Food]()
> // rdd0 and rdd1 should have the same elements
> {code}
> I originally submitted a smaller PR for spark-csv
> <https://github.com/databricks/spark-csv/pull/52>, but Reynold Xin suggested
> that converting a DataFrame to a typed RDD wasn't something specific to
> spark-csv.
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